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E-raamat: Spatio-Temporal Models for Ecologists

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"Ecological dynamics are tremendously complicated and are studied at a variety of spatial and temporal scales. Ecologists often simplify analysis by describing changes in density of individuals across a landscape, and statistical methods are advancing rapidly for studying spatio-temporal dynamics. However, spatio-temporal statistics is often presented using a set of principles that may seem very distant from ecological theory or practice. This book seeks to introduce a minimal set of principles and numerical techniques for spatio-temporal statistics that can be used to implement a wide range of real-world ecological analyses regarding animal movement, population dynamics, community composition, causal attribution, and spatial dynamics. We provide a step-by-step illustration of techniques that combine core spatial-analysis packages in R with low-level computation using Template Model Builder. Techniques are showcased using real-world data from varied ecological systems, providing a toolset for hierarchical modelling of spatio-temporal processes. Spatio-Temporal Models for Ecologists is meant for graduate level students, alongside applied and academic ecologists"--

This book introduces a minimal set of principles and numerical techniques for spatio-temporal statistics that can be used to implement a wide range of real-world ecological analyses regarding animal movement, population dynamics, community composition, causal attribution, and spatial dynamics.



Ecological dynamics are tremendously complicated and are studied at a variety of spatial and temporal scales. Ecologists often simplify analysis by describing changes in density of individuals across a landscape, and statistical methods are advancing rapidly for studying spatio-temporal dynamics. However, spatio-temporal statistics is often presented using a set of principles that may seem very distant from ecological theory or practice. This book seeks to introduce a minimal set of principles and numerical techniques for spatio-temporal statistics that can be used to implement a wide range of real-world ecological analyses regarding animal movement, population dynamics, community composition, causal attribution, and spatial dynamics. We provide a step-by-step illustration of techniques that combine core spatial-analysis packages in R with low-level computation using Template Model Builder. Techniques are showcased using real-world data from varied ecological systems, providing a toolset for hierarchical modelling of spatio-temporal processes. Spatio-Temporal Models for Ecologists is meant for graduate level students, alongside applied and academic ecologists.

Key Features:

  • Foundational ecological principles and analyses
  • Thoughtful and thorough ecological examples
  • Analyses conducted using a minimal toolbox and fast computation
  • Code using R and TMB included in the book and available online

Part 1: Introductory
1. Statistical models for individual-based processes
2. Hierarchical models and Laplace approximation Part 2: Basic
3. Population dynamics and state-space models
4. Individual movement
5. Spatial models
6. Spatial sampling designs and analysis
7. Covariates affecting densities and detectability Part 3: Advanced
8. Spatio-temporal models with seasonal or multi-year dynamics
9. Ecological teleconnections
10. Population movement and habitat selection
11. Multispecies models for community diversity and biogeography
12. A decadal forecast for spatio-temporal models A. Acknowledgements B. Appendices

James Thorson is a statistical ecologist at the Alaska Fisheries Science Center within the National Marine Fisheries Service. His research interests include population dynamics, life-history theory, and methods for the sustainable management of natural resources. He has taught graduate-level courses in hierarchical modelling and spatio-temporal statistics at University of Washington.

Kasper Kristensen is a Senior Researcher at Danish Technical University. His research interests include spatio-temporal statistics and computational methods. He developed the R-package TMB, which is seeing increased use throughout ecology. For example, TMB is the computational backend for R-package glmmTMB, which has been cited over 3000 times from 2017-2022.
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